GTM World Model Builder★ FinalistDeep-reviewed
by Anna Yuan
What they're building
ScaleAgentic builds Scout – the GTM Brain for revenue teams. Give Scout a revenue goal, and it decides what motion to run, who to target, which signals to trust, how to execute across agents and tools, and how to learn from outcomes. Over time, Scout builds a company-specific GTM World Model that learns how each company wins. For this demo, we built GTM World Model Builder: the front door into Scout. It starts with a company website and revenue goal, then builds the first version of a GTM World Model – mapping company context, ICP, buying signals, target accounts, and recommended revenue motion. Scout then turns that model into an Early Signal Detection → Agentic ABM workflow: which accounts matter, why now, what motion to run, and how the system improves from feedback. Not another tool. A GTM Decision and Operating system.
AI code reviewrepo: no-repo
No verifiable build. The submission provides no repo_url (only the org github.com/ScaleAgentic); the org's named repo 'world-model-builder' is empty (size 0, 'This repository is empty'), and GitHub code search across all three org repos returns zero hits for tavily/nebius/composio. The demo (helixmax.vercel.app) renders only a bare 'Helix Max - GTM Command Center' heading with no functional UI, and the site (scaleagentic.ai) is a 'Request Access' marketing landing page that isn't the product and names no sponsors. Per the rubric, a landing page that isn't the product plus an empty/absent repo is a NO BUILD, and there is no sponsor code to credit. ⚑ No clonable repo in submission; org repo empty; demo is a title-only page; site is marketing-only; no demo video; no sponsor SDK usage found anywhere.